With the recent explosion of information, the amount of information on the internet has expanded, with the scale of regular data bases and file systems reaching intractable sizes. The challenge of finding useful information for users is that, if a search query is cast too narrow, some useful information may be missed and overlooked, and while on the other hand, if the search query expression is cast too wide, some useful information would be buried deep inside the search results among more useless information. For example, a user needs to search for the information on the Intelligent Network (IN). He is also particularly interested in applying the IN technology to the CDMA system, while learning about the IN technology in general. If the search query is set as “Intelligent network AND CDMA” as the current art doing, the results would be limited to a narrower set than expected, but if the query is “Intelligent network”, then the results are too varied and more pertinent information related to CDMA technology would get lost among the more general results.
In the current manifestation of the internet search technologies, like Google, for example rankings of the search results are based on the perceived “importance of web pages” through the analysis of hyper-linked relationships among those pages. With this technology, the ranking rules are predefined by the system and user-specified interests have no impact on the ranking of the results. In other words, the user's searching demand is not being customized.
Therefore, a mechanism is needed to re-rank the search results based on the user's interest and render the most relevant part of the results at the top while maintaining the number of the search results without reducing it. With this novel mechanism, the user is able to find the information he expects most, while keeping the other information available. Also, by applying a different set of re-ranking expressions to the same set of search results, the user can get multiple re-sorted views that are re-ranked based on his different interests. In this way, the user's searching experience has been enhanced by using his personal interests as a customization factor.